Evidence map›Paper›PMID 35744374›Full record

ReviewMaterials (Basel, Switzerland)2022

Recent Advances in Materials for Wearable Thermoelectric Generators and Biosensing Devices.

Maria Sattar, Woon-Hong Yeo

Open access · goldAbstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Recent Advances in Air-StableMaterials (Basel, Switzerland) · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Maria SattarGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Woon-Hong YeoGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.ORCID 0000-0002-5526-3882
Georgia Institute of Technology · US

Funding

Georgia Institute of Technology n/a
6 · The paper itself

Abstract

Recently, self-powered health monitoring systems using a wearable thermoelectric generator (WTEG) have been rapidly developed since no battery is needed for continuous signal monitoring, and there is no need to worry about battery leakage. However, the existing materials and devices have limitations in rigid form factors and small-scale manufacturing. Moreover, the conventional bulky WTEG is not compatible with soft and deformable tissues, including human skins or internal organs. These limitations restrict the WTEG from stabilizing the thermoelectric gradient that is necessary to harvest the maximum body heat and generate valuable electrical energy. This paper summarizes recent advances in soft, flexible materials and device designs to overcome the existing challenges. Specifically, we discuss various organic and inorganic thermoelectric materials with their properties for manufacturing flexible devices. In addition, this review discusses energy budgets required for effective integration of WTEGs with wearable biomedical systems, which is the main contribution of this article compared to previous articles. Lastly, the key challenges of the existing WTEGs are discussed, followed by describing future perspectives for self-powered health monitoring systems.

Indexed as

energy harvestingnanogeneratorself-powered systemthermoelectric materialwearable device

Identifiers

PMID35744374
PMCPMC9230808
OpenAlexW4283124435

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.